Estadísticas Básicas

Column

Sumario General I

      CODIGO                           NOMBRE_FUENTE      COTA     
 49949-06: 1   Captación Huacoto              : 1    Min.   :3217  
 49949-07: 1   Captación Piscigranja/Huacoto 2: 1    1st Qu.:3450  
 49949-08: 1   Galéria Marashuayco            : 1    Median :3549  
 49949-10: 1   Galéria Pillao Matao           : 1    Mean   :3586  
 49949-11: 1   Galería Salkantay              : 1    3rd Qu.:3755  
 49949-12: 1   Galería Saqramayo              : 1    Max.   :4077  
 (Other) :26   (Other)                        :26                  
      Lito1                                   USO_FUENTE  TEMPERATURA   
 arenisca:16   consumo humano                      :12   Min.   : 9.40  
 caliza  : 2   industrial                          : 1   1st Qu.:11.97  
 grava   : 7   lavado de ropa y autos              : 5   Median :13.50  
 limo    : 3   piscigranja                         : 1   Mean   :14.03  
 limolita: 1   riego de vegetales                  :10   3rd Qu.:15.68  
 lutita  : 1   riego de vegetales\r\nconsumo humano: 1   Max.   :23.30  
 yesos   : 2   sin uso                             : 2                  
       pH              CE              TDS           Salinidad     
 Min.   :6.000   Min.   : 241.8   Min.   : 119.0   Min.   :0.0970  
 1st Qu.:7.000   1st Qu.: 400.6   1st Qu.: 192.2   1st Qu.:0.2308  
 Median :7.115   Median : 773.2   Median : 379.4   Median :0.3850  
 Mean   :7.224   Mean   : 829.1   Mean   : 425.0   Mean   :0.4342  
 3rd Qu.:7.503   3rd Qu.:1081.8   3rd Qu.: 667.2   3rd Qu.:0.5817  
 Max.   :8.080   Max.   :2171.0   Max.   :1050.0   Max.   :1.1420  
                                                                   
  Resistividad          RDO              OD        
 Min.   :  0.600   Min.   :1.260   Min.   : 18.80  
 1st Qu.:  1.485   1st Qu.:5.045   1st Qu.: 76.20  
 Median :  2.644   Median :5.660   Median : 88.40  
 Mean   :185.983   Mean   :5.358   Mean   : 80.35  
 3rd Qu.:467.600   3rd Qu.:6.330   3rd Qu.: 93.65  
 Max.   :833.900   Max.   :7.850   Max.   :121.30  
                                                   

Sumario General II

                   HIDROTIPO          FLUJO         long       
 bicarbonatada calcica  : 9   subterraneo:29   Min.   :-72.02  
 bicarbonatada magnesica: 1   superficial: 3   1st Qu.:-71.97  
 sulfatada calcica      :22                    Median :-71.95  
                                               Mean   :-71.94  
                                               3rd Qu.:-71.91  
                                               Max.   :-71.83  
      lat        
 Min.   :-13.60  
 1st Qu.:-13.57  
 Median :-13.55  
 Mean   :-13.54  
 3rd Qu.:-13.51  
 Max.   :-13.47  

Sumario de Parámetros Físico-Químicos

Análisis CE-Hidrotipo

Análisis CE-Composición

Análisis CE-Composición-Hidrotipo

Análisis Geoespacial de Parámetros Físico-Químico

Column

Geomap Puntos Hidroquímica

---
title: "Caracterización Hidroquímica"
author: "Desarrolladores: A.Otiniano & J.Andrade - Expositor:M.Ccopa"
output:
  flexdashboard::flex_dashboard:
    orientation: columns
    theme: lumen
    source_code: embed
  html_document:
    df_print: paged
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = FALSE, message = FALSE, warning = FALSE)
library(readxl);library(flexdashboard) ; library(crosstalk) ; library(tidyverse) ; library(plotly); library(sf); library(mapview); library(DT); library(readxl); library(tmap); library(linemap); library(rgdal);library(leaflet.extras); library(crosstable);
library(psych); library(data.table); library(leaflet.providers); library(leafem)
library(leafsync)
Sys.setenv('MAPBOX_TOKEN' = 'pk.eyJ1IjoiYWxvbnNvMjUiLCJhIjoiY2tveGJseXJpMGNmcDJ3cDhicmZwYmY3MiJ9.SbThU_R8YGE1Zll-nNrZKA')
```

```{r}
Cusco <- read_xlsx(path="BD/BD_Cusco.xlsx", col_names = TRUE)
data01<-Cusco[ ,c("NORTE","ESTE")]
data01<-data01[ ,order(c(names(data01)))]
sputm <- SpatialPoints(data01, proj4string=CRS("+proj=utm +zone=19 +south +datum=WGS84")) 
spgeo <- spTransform(sputm, CRS("+proj=longlat +datum=WGS84"))
spgeo <- as.data.frame(spgeo)
colnames(spgeo)<-c("long","lat")
Cusco<-cbind(Cusco,spgeo)
Cusco$CODIGO <- as.factor(Cusco$CODIGO)
Cusco$NOMBRE_FUENTE <- as.factor(Cusco$NOMBRE_FUENTE)
Cusco$DISTRITO <- as.factor(Cusco$DISTRITO)
Cusco$TIPO_FUENTE <- as.factor(Cusco$TIPO_FUENTE)
Cusco$USO_FUENTE <- as.factor(Cusco$USO_FUENTE)
Cusco$Lito1 <- as.factor(Cusco$Lito1)
Cusco$Lito2 <- as.factor(Cusco$Lito2)
Cusco$Lito3 <- as.factor(Cusco$Lito3)
Cusco$COLOR <- as.factor(Cusco$COLOR)
Cusco$OLOR <- as.factor(Cusco$OLOR)
Cusco$FLUJO <- as.factor(Cusco$FLUJO)
Cusco$HIDROTIPO <- as.factor(Cusco$HIDROTIPO)
Cusco$SIMBOLO <- as.factor(Cusco$SIMBOLO)
Cusco$RANGO_DUREZA <- as.factor(Cusco$RANGO_DUREZA)
```

Estadísticas Básicas
=======================================================================

Column {.tabset}
-------------------------------------

### Sumario General I

```{r}
Cusco_fq <- Cusco %>% select("CODIGO","NOMBRE_FUENTE","COTA","Lito1",
                           "USO_FUENTE","TEMPERATURA","pH","CE",
                           "TDS", "Salinidad","Resistividad",
                           "RDO","OD",
                           "HIDROTIPO","FLUJO",
                           "long", "lat")
summary(Cusco_fq[ ,1:13])
```

### Sumario General II

```{r}
summary(Cusco_fq[ ,14:ncol(Cusco_fq)])
```


### Sumario de Parámetros Físico-Químicos

```{r}

estadisticos <- function(col){
  
  norm_test <- shapiro.test(col)
  value <- c(round(length(col),3),round(sum(is.na(col))),round(min(col,na.rm=TRUE),3),
             round(max(col,na.rm=TRUE),3),
             round(quantile(col, 0.05,na.rm=TRUE),3),
               round(quantile(col, 0.25,na.rm=TRUE),3), round(mean(col,na.rm=TRUE),3), round(median(col,na.rm=TRUE),3),
               round(mean(col,trim = 0.10,na.rm=TRUE),3),
               round(quantile(col, 0.75,na.rm=TRUE),3), 
             round(quantile(col, 0.95,na.rm=TRUE),3),
             round(IQR(col,na.rm=TRUE),3),
               round(mad(col,na.rm=TRUE),3),
               round(sd(col,na.rm=TRUE),3),round(skew(col,na.rm=TRUE),3), round(kurtosi(col,na.rm=TRUE),3), 
               round((sd(col,na.rm=TRUE)/mean(col,na.rm=TRUE))*100,3),
               norm_test$statistic, norm_test$p.value)

}
statistic <- c("N","Nulos","Minimo", "Maximo","P5 (5%)","Q1 (25%)","Media Aritmetica","Mediana",
                   "Trimmed mean (10%)","Q3 (75%)","P95 (95%)", "RIQ","MAD","Sd","As","K","CV",
                   "Shapiro statistic", "Shapiro p-valor")
T2PRO <- sapply(Cusco_fq[ ,c("TEMPERATURA","pH","CE",
                           "TDS", "Salinidad","Resistividad",
                           "RDO","OD")], estadisticos)
rownames(T2PRO) <- statistic

datatable(T2PRO, filter = "top")
```

### Análisis CE-Hidrotipo

```{r}
Filtro2 <- Cusco %>% 
  group_by(HIDROTIPO) %>% 
  summarise(
    n = n(),
    min.ce = round(min(CE, na.rm = FALSE),1),
    mean.ce = round(mean(CE, na.rm = FALSE), 1),
    ce.50    = quantile(CE, probs = 0.50, na.rm =FALSE),
    ce.75    = quantile(CE, probs = 0.75, na.rm =FALSE),
    max.ce = max(CE, na.rm = FALSE)
  ) %>%
  arrange(desc(min.ce))
datatable(Filtro2, filter = "top")
```

### Análisis CE-Composición

```{r}
Filtro3 <- Cusco %>% 
  group_by(Lito1) %>% 
  summarise(
    n = n(),
    min.ce = round(min(CE, na.rm = FALSE),1),
    mean.ce = round(mean(CE, na.rm = FALSE), 1),
    ce.50    = quantile(CE, probs = 0.50, na.rm =FALSE),
    ce.75    = quantile(CE, probs = 0.75, na.rm =FALSE),
    max.ce = max(CE, na.rm = FALSE)
  ) %>%
  arrange(desc(min.ce))
datatable(Filtro3, filter = "top")
```

### Análisis CE-Composición-Hidrotipo

```{r}
Filtro4 <- Cusco %>% 
  group_by(Lito1,HIDROTIPO) %>% 
  summarise(
    n = n(),
    min.ce = round(min(CE, na.rm = FALSE),1),
    mean.ce = round(mean(CE, na.rm = FALSE), 1),
    ce.50    = quantile(CE, probs = 0.50, na.rm =FALSE),
    ce.75    = quantile(CE, probs = 0.75, na.rm =FALSE),
    max.ce = max(CE, na.rm = FALSE)
  ) %>%
  arrange(desc(min.ce))
datatable(Filtro4, filter = "top")
```

Análisis Geoespacial de Parámetros Físico-Químico
=======================================================================

Inputs {.sidebar}
-----------------------------------------------------------------------

```{r}
Cusco_fq$colors <- factor(Cusco_fq$HIDROTIPO, levels = unique(Cusco_fq$HIDROTIPO))
cols <- c(rgb(255,255,0,maxColorValue = 255),
                                  rgb(50,74,178,maxColorValue = 255),
                                  rgb(0,176,242,maxColorValue = 255))
sd <- SharedData$new(Cusco_fq)
```

```{r}
filter_slider("TEMPERATURA", "T(ºC)", sd, ~TEMPERATURA)
filter_slider("pH", "Potencial Hidrógeno", sd, ~pH)
filter_slider("CE", "Conductividad Eléctrica (uS/cm)", sd, ~CE)
filter_slider("TDS", "TDS", sd, ~TDS)
filter_slider("Resistividad", "Resistividad (ohm.m)", sd, ~Resistividad)
filter_select("Lito1", "Composición Geológica", sd, ~Lito1)
```

Column
-------------------------------------

### Geomap Puntos Hidroquímica

```{r}
plot_mapbox(sd, x = ~long, y = ~lat) %>%
  add_markers(
            split = ~HIDROTIPO, color = ~colors, colors = cols , 
            marker = list(size = 15),
            text = ~paste(paste("Codigo:", CODIGO), paste("Nombre:", NOMBRE_FUENTE),
                          paste("Cota(m):", COTA), paste("FLUJO:", FLUJO),
                          paste("Composicion:", Lito1), paste("HIDROTIPO:", HIDROTIPO),
                          paste("CE (uS/cm):", CE), sep = "
"), mode = "scattermapbox", hoverinfo = "text") %>% layout(title = 'Analisis Hidroquímico', font = list(color='white'), plot_bgcolor = '#191A1A', paper_bgcolor = '#191A1A', legend = list(orientation = 'h', font = list(size = 8)), mapbox= list( style = "mapbox://styles/alonso25/ckppwz4o617pf17pn6iibpsku", sourcetype = 'vector', zoom = 9, showleyend = TRUE, center = list(lat = ~median(lat), lon = ~median(long)))) %>% highlight(on = "plotly_selected",off = "plotly_deselect", dynamic = FALSE, color = "red") ```